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Research map / Vision-language and multimodal / Human and embodied modeling

Diverse Beam Search for Improved Description of Complex Scenes

AAAI 2018 · Vision-language and multimodal › Human and embodied modeling · approach: Scene graph generation · 229 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
replace beam search with diverse beam searchcaptioning LSTM · COCOOracle SPICE@20: 27.34 -> 28.09Helped
replace beam search with diverse beam searchcaptioning LSTM · COCOdistinct 4-grams: 5.67 -> 13.44Helped
replace BS with DBS on harder imagescaptioning LSTM · COCO by image complexityOracle SPICE@20 gain: 0.67 / 0.91 / 1.13Helped
replace BS with DBScaptioning LSTM · PASCAL-50SOracle SPICE@20: 8.74 -> 9.293Helped
replace BS with DBSVQG model · VQGSPICE: 15.17 -> 16.49Helped
replace BS with DBSGRU NMT · En-Fr newstest-2013BLEU-4: 13.52 -> 13.69Helped
DBS vs Li et al. (2015) MMI decodingGRU NMT · En-Fr newstest-2013Oracle BLEU-4@20: 18.86 -> 18.77Hurt
replace BS with DBScaptioning LSTM · COCO human studyhuman preference: 60%Helped
use hamming diversity instead of n-gram, cumulative or embedding diversity (ablation)DBS · PASCAL-50SOracle CIDEr@kHelped
set groups G=B (max exploration) vs G=1 (ablation)DBS · validationoracle accuracyHelped

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